东营云计算系统架构关键技术的研究

云计算是一种新的用户体验和业务模式,它是在分布式计算的基础上发展而来的,黄河三角洲云计算中心是东营创建智慧城市的积极尝试。介绍云计算的概念、特点和云计算的系统架构,以IBM的云计算技术为例,结合黄河三角洲云计算中心,研究云平台系统架构的关键技术,指出了云计算的发展趋势。     

Annotation-based access control for collaborative information spaces

Web 2.0 social platforms (e.g., Flickr, YouTube) and Collaborative Working Environments (e.g., Microsoft SharePoint, BSCW) provide Web-based collaborative information spaces which enable common users and/or professionals to work together and share their online resources. Most of these collaborative information spaces provide role-based or group-based, coarse-grained access control policies which cannot successfully cope with the requirements posed by massive and open collaboration. In this paper, we present an annotation-based access control (AnBAC) model supported by a Collaboration Vocabulary (CoVoc) as a more flexible and user-centric access control approach. Based on this, we developed two tools: Uncle-Share is a gadget that provides annotation-based access control and can be equipped with CoVoc for annotating collaborative relationships. Who-With-Whom uses CoVoc to visualize extended social networks in order to help users to select appropriate contacts to grant access to resources.     

On-demand minimum cost benchmarking for intermediate dataset storage in scientific cloud workflow systems

Many scientific workflows are data intensive: large volumes of intermediate datasets are generated during their execution. Some valuable intermediate datasets need to be stored for sharing or reuse. Traditionally, they are selectively stored according to the system storage capacity, determined manually. As doing science on clouds has become popular nowadays, more intermediate datasets in scientific cloud workflows can be stored by different storage strategies based on a pay-as-you-go model. In this paper, we build an intermediate data dependency graph (IDG) from the data provenances in scientific workflows. With the IDG, deleted intermediate datasets can be regenerated, and as such we develop a novel algorithm that can find a minimum cost storage strategy for the intermediate datasets in scientific cloud workflow systems. The strategy achieves the best trade-off of computation cost and storage cost by automatically storing the most appropriate intermediate datasets in the cloud storage. This strategy can be utilised on demand as a minimum cost benchmark for all other intermediate dataset storage strategies in the cloud. We utilise Amazon clouds’ cost model and apply the algorithm to general random as well as specific astrophysics pulsar searching scientific workflows for evaluation. The results show that benchmarking effectively demonstrates the cost effectiveness over other representative storage strategies.     

Image segmentation based on histogram analysis utilizing the cloud model

Both the cloud model and type-2 fuzzy sets deal with the uncertainty of membership which traditional type-1 fuzzy sets do not consider. Type-2 fuzzy sets consider the fuzziness of the membership degrees. The cloud model considers fuzziness, randomness, and the association between them. Based on the cloud model, the paper proposes an image segmentation approach which considers the fuzziness and randomness in histogram analysis. For the proposed method, first, the image histogram is generated. Second, the histogram is transformed into discrete concepts expressed by cloud models. Finally, the image is segmented into corresponding regions based on these cloud models. Segmentation experiments by images with bimodal and multimodal histograms are used to compare the proposed method with some related segmentation methods, including Otsu threshold, type-2 fuzzy threshold, fuzzy C-means clustering, and Gaussian mixture models. The comparison experiments validate the proposed method.     

SecondSkin: An interactive method for appearance transfer

SecondSkin estimates an appearance model for an object visible in a video sequence, without the need for complex interaction or any calibration apparatus. This model can then be transferred to other objects, allowing a non‐expert user to insert a synthetic object into a real video sequence so that its appearance matches that of an existing object, and changes appropriately throughout the sequence. As the method does not require any prior knowledge about the scene, the lighting conditions, or the camera, it is applicable to video which was not captured with this purpose in mind. However, this lack of prior knowledge precludes the recovery of separate lighting and surface reflectance information. The SecondSkin appearance model therefore combines these factors. The appearance model does require a dominant light‐source direction, which we estimate via a novel process involving a small amount of user interaction. The resulting model estimate provides exactly the information required to transfer the appearance of the original object to new geometry composited into the same video sequence.     

Amoeba-based Chaotic Neurocomputing: Combinatorial Optimization by Coupled Biological Oscillators

We demonstrate a neurocomputing system incorporating an amoeboid unicellular organism, the true slime mold Physarum, known to exhibit rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. Introducing optical feedback applied according to a recurrent neural network model, we induce that the amoeba’s photosensitive branches grow or degenerate in a network-patterned chamber in search of an optimal solution to the traveling salesman problem (TSP), where the solution corresponds to the amoeba’s stably relaxed configuration (shape), in which its body area is maximized while the risk of being illuminated is minimized.Our system is capable of reaching the optimal solution of the four-city TSP with a high probability. Moreover, our system can find more than one solution, because the amoeba can coordinate its branches’ oscillatory movements to perform transitional behavior among multiple stable configurations by spontaneously switching between the stabilizing and destabilizing modes. We show that the optimization capability is attributable to the amoeba’s fluctuating oscillatory movements. Applying several surrogate data analyses, we present results suggesting that the amoeba can be characterized as a set of coupled chaotic oscillators.

Applying web-enabled self-regulated learning and problem-based learning with initiation to involve low-achieving students in learning

Vocational degree earners represent a major portion of the work force in Taiwan. However, vocational education in Taiwan is highly competitive in that it must attract sufficient student enrollment in an environment with a rapidly increasing number of schools. In this context, many vocational students tend to have lower levels of academic achievement. Under such constraints but moving toward more practical orientation, the authors conducted a quasi-experiment to examine the effects of applying web-based self-regulated learning (SRL), web-based problem-based learning (PBL) with initiation, and their combination to help these low-achieving students be involved positively in their learning. Four classes in successive years, with a total of 177 third-year students, were divided into 2 (SRL vs. non-SRL) × 2 (PBL with initiation vs. PBL without initiation) experimental groups. Results were generally positive. The authors further discuss the implications for schools, particularly vocational schools, and for scholars and teachers concerned about e-learning.     

基于龙芯2E的AMC处理器模块设计

介绍基于国产通用处理器的嵌入式高级夹层卡（AMC）处理器模块的设计和实现。该模块以龙芯2ECPU为核心,板卡设计符合AMC规范,可以直接应用于符合新型先进电信计算构架规范的计算机系统。模块配有适用于嵌入式系统互联的串行RapidIO接口,可以提供充足的有效带宽用于数据通信和系统配置。给出模块的芯片组设计和软件配置。     

基于Web Service的虚拟研究中心KMS构建

针对虚拟研究中心知识管理敏捷化、柔性化和分布式的需求特性,结合Web Service技术搭建了虚拟研究中心知识管理系统网络体系架构,提出一种基于Web Service的虚拟研究中心知识管理系统模型。依据模型框架,构建雅砻江水电开发虚拟研究中心知识管理系统。研究表明,依据模型构建的虚拟研究中心知识管理系统能有效地实现基于Web的知识共享、交流和创新,模型具有较好的可靠性和可行性。